The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
Defining and Improving Data Quality in Medical Registries: A Literature Review, Case Study, and Generic Framework
Open accessAbstract
Over the past years the number of medical registries has increased sharply. Their value strongly depends on the quality of the data contained in the registry. To optimize data quality, special procedures have to be followed. A literature review and a case study of data quality formed the basis for the development of a framework of procedures for data quality assurance in medical registries. Procedures in the framework have been divided into procedures for the co-ordinating center of the registry (central) and procedures for the centers where the data are collected (local). These central and local procedures are further subdivided into (a) the prevention of insufficient data quality, (b) the detection of imperfect data and their causes, and (c) actions to be taken / corrections. The framework can be used to set up a new registry or to identify procedures in existing registries that need adjustment to improve data quality.
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Citations
Cites
Le Gall, J.-R. (1993) · JAMA: The Journal of the American Medical Association · doi:10.1001/jama.270.24.2957 · Cited by 7,773
Anchoring Data Quality Dimensions in Ontological Foundations
Wand, Y., & Wang, R. Y. (1996) · Communications of the ACM · doi:10.1145/240455.240479 · Cited by 1,479
Quality of data in the Manchester orthopaedic database.
Barrie, J. L., & Marsh, D. R. (1992) · BMJ · doi:10.1136/bmj.304.6820.159 · Cited by 74
Cited by
Carmona, L., Gómez‐Reino, J. J., Rodríguez‐Valverde, V., Montero, D., Pascual‐Gómez, E., Mola, E. M., Carreño, L., Figueroa, M., & BIOBADASER Group (2005) · Arthritis & Rheumatism · doi:10.1002/art.21043 · Cited by 656
Defining and measuring completeness of electronic health records for secondary use
Weiskopf, N. G., Hripcsak, G., Swaminathan, S., & Weng, C. (2013) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2013.06.010 · Cited by 367
“, based a priori upon the content) or extrinsic requirements (based upon the use) [11,12].”
Connolly, A., Gaehl, E., Martin, H., Morris, J., & Purandare, N. (2011) · Aging & Mental Health · doi:10.1080/13607863.2011.596805 · Cited by 307
Stow, P. J., Hart, G. K., Higlett, T., George, C., Herkes, R., McWilliam, D., & Bellomo, R. (2006) · Journal of Critical Care · doi:10.1016/j.jcrc.2005.11.010 · Cited by 272
Kahn, M. G., Raebel, M. A., Glanz, J. M., Riedlinger, K., & Steiner, J. F. (2012) · Medical Care · doi:10.1097/mlr.0b013e318257dd67 · Cited by 260
Metadata
- Authors
- Arts, D. G. T.
- Venue
- Journal of the American Medical Informatics Association
- Publisher
- Oxford University Press (OUP)
- Published
- 2002-07-23
- Volume
- 9
- Issue
- 6
- Pages
- 600-611
- ISSN
- 1067-5027 (ISSN-L)
- 1527-974X
- OpenAlex
- W2167025863
- Cited by
- 597
- References
- 3
- FWCI
- 15.65
- Type
- journal article
- Language
- en
- Open access
- green
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- CoChat. (2026). Citation check: Defining and Improving Data Quality in Medical Registries: A Literature Review, Case Study, and Generic Framework. https://app.cochat.ai/papers/10.1197/jamia.m1087
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- Arts, D. G. T. (2002). Defining and Improving Data Quality in Medical Registries: A Literature Review, Case Study, and Generic Framework. Journal of the American Medical Informatics Association. https://doi.org/10.1197/jamia.m1087
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
